The present invention generally relates to wireless communications receivers, and more particularly relates to techniques for suppression of interfering signals to improve receiver performance.
The data rate that can be supported between two devices in a wireless communication system is very often limited by interference from nearby transmitters utilizing the same spectrum. Specifically, for the downlink (base station to wireless terminal transmissions) in a wireless cellular network, receiver performance at the targeted wireless terminal is often limited by interference from other cells. Similar problems apply to the base station receiver, for uplink transmissions.
The impact of interference from other cells can be characterized in terms of a “geometry factor.” The geometry factor is defined as the total received power from the serving cell divided by the receiver power from all other neighbor cell base stations on the same carrier frequency. Since other base stations largely will be perceived as noise, the geometry factor thus is a measure of the current signal-to-noise (SNR) operating point of the device. For instance, a wireless terminal near a cell edge may receive transmissions at similar strengths from the serving base station and from one or more neighboring cells, leading to a low geometry factor for the desired own-cell signal. This can be seen in FIG. 1, where wireless terminal or user equipment (UE) 120 is served by base station 110, but is near the edge of the cell. As a result, wireless terminal 120 suffers interference from signals transmitted by another base station 130, which is serving wireless terminal or user equipment (UE) 140. Other-cell interference is often the dominant impairment even for wireless terminals not located at or near a cell border.
The bulk of the interference contributed by the other cell(s) is typically due to traffic data transmission. By reducing the effective power of such interference, the effective geometry factor for the own-cell signal may be improved and performance gains achieved. Several techniques may be used to mitigate the interference.
One category of these techniques is linear interference suppression. If the UE has several receiver antennas, the effective antenna lobe for the receiver may be steered so as to point a spatial null in the direction of arrival for the dominant interfering signal, leading to improved signal-to-interference-plus-noise ratios (SINR) for the desired signal. Statistics of the received signal are used to determine receiver combining weights that lead to the desired spatial pattern. Techniques for this, such as several variations of interference rejection combining (IRC) algorithms, are well known.
Another category of interference-mitigation techniques is interference cancellation. With these techniques, all or part of the interfering signal is reconstructed and explicitly subtracted from the received signal. In a simple successive interference-cancellation receiver, the interfering signal may be demodulated and/or decoded. The resulting bit sequence is used to reconstruct the transmitted interfering symbol sequence. This symbol sequence is then filtered to mimic the effects of the interfering signal's channel and subtracted from the received signal. After that, the desired signal is demodulated and decoded, with better quality than would have been possible without the interference cancelling step.
Another approach to reducing the effect of interfering signals is joint demodulation of the desired signal and an interfering signal. With this approach, several received signal components are considered jointly in demodulation. (The terms “joint demodulation” and “joint detection” are used interchangeably herein, to refer to this general technique.) A multitude of received symbol hypotheses are formed, corresponding to the multiple possible symbols that have been transmitted through the end-to-end propagation channel. The symbol to be detected thus becomes a higher-dimensional super-symbol, which includes the interactions of the signals to be jointly detected. Maximum-likelihood detection (MLD) or near-MLD algorithms may be used to perform the demodulation.
While all of these forms of interference mitigation may provide performance gains across a wide variety of scenarios, the largest gains are typically available when the signal structure and the transport format of the interfering signals is known. For example, the interference-cancellation and joint-demodulation approaches require knowledge of resource allocation, such as the codes used by interfering signals in code-division multiple access (CDMA) systems (e.g., in High-Speed Downlink Packet Access, or HSDPA, systems), or the resource blocks allocated to interfering signals in Orthogonal Frequency-Division Multiplexing (OFDM) systems (e.g., in the 3rd-Generation Partnership Project's Long-Term Evolution, or LTE, systems). These approaches also work best when the details of the modulation technique used for the interfering signals (e.g., a Quadrature-Amplitude Modulation, or QAM, mode) are known, and/or when the details of a Multiple-Input Multiple-Output (MIMO) configuration, such as the transmission rank and precoding vectors, are known. Furthermore, when the interference-suppressing receiver uses iterative (Turbo) decoding techniques, knowledge of the transport block format (TFRC) for an interfering signal allows the channel coding gain present in the interfering signal to be used to obtain the best possible signal estimate for subtraction. In various wireless systems, this information (transport block formats, resource allocations, etc.) is conveyed via downlink control channels, such as the High-Speed Shared Control Channel (HS-SCCH) in HSDPA systems and the Physical Downlink Control Channel (PDCCH) in LTE systems.
A variety of advanced receiver structures exist to combat interference and improve the geometry factor for the desired signal. In one solution for an interference-mitigating receiver, the signal quality for the desired signal and the signal quality for the interfering signal (e.g. SINR) are both estimated. Decoding of the interfering users' control messages is then attempted. Depending on the signal qualities and the information available from the control messages regarding resource allocation and transport formats, a suitable receiver configuration may be chosen to carry out interference mitigation.
To decode a control message meant for another user, a wireless terminal-specific index (UE ID in HSDPA, RNTI in LTE) for the other user is typically required to de-mask the control message. While this information may not be openly available in the network, it may be inferred using blind detection approaches. Other neighbor cell configuration information required for demodulation of the control channel signals for another user is often available to a mobile terminal via neighbor-cell list information in higher-layer signaling. This assumption is also made by a parametric Type 3i receiver specified in 3GPP RAN4 for HSDPA, and is necessary for conducting standard wireless terminal measurements, such as for reporting neighbor-cell received-signal code power (RSCP).